1. Field of the Invention
This invention relates generally to a system and method of determining nitrogen levels from a digital image, and more particularly to a system and method of determining leaf nitrogen concentration and/or crop yield from a digital image of fully developed leaves (collared leaf) of a crop of nonlegumes, such as corn, rice, wheat, cotton, potatoes or sugarcane.
2. Description of the Related Art
Management of fertilizer nitrogen is a critical component for producing consistent crop yields. Nitrogen fertilizer also represents a considerable input cost and has serious environmental consequences if over applied. Therefore, it is important to apply the correct amount of fertilizer to meet the crop's need but not to supply more than is required because of the cost and environmental concerns.
There are few tools that are currently available to help farmers determine if crop nitrogen levels during the season are adequate, and several techniques have been used to objectively measure crop color, including reflectance measurements, chlorophyll and amino acid analysis, and comparison with standardized colors. All of these techniques have certain disadvantages compared with subjective color ratings. Reflectance, chlorophyll, and amino acid measurements all require relatively expensive equipment, and transport of samples to a laboratory for analysis. In addition, correlations between color and chlorophyll or amino acid measurements are either species or cultivar dependent. A hand-held SPAD meter (Minolta) gives real-time chlorophyll concentration of leaves in the field, and chlorophyll concentration has a close relationship to leaf nitrogen concentration. In the Midwest, SPAD meter measurements are closely associated with leaf nitrogen and have a positive relationship with yield. (Schepers, et al., “Comparison of corn leaf nitrogen concentration and CM readings.” Commun. Soil Sci. Plant Anal. 1992, 23:2173-87; Scharf, et al., “Chlorophyll meter readings can predict nitrogen needs and yield in response of corn in North-Central USA.” Agron. J. 2006, 98:655-65). Disadvantages of the SPAD meter include a large initial equipment cost and that a large number of measurements may be required to make a representative measurement.
In recent years, digital photography has become a common and affordable means for the scientific community to document and present images. Digital cameras, in conjunction with image analysis software, are being used to quantify wheat (Triticum aestivum L.) senescence (Adamsen, et al., “Measuring wheat senescence with a digital camera.” Crop Sci. 1999, 39:719-724) and canopy coverage in wheat (Lukina, et al., “Estimating vegetation coverage in wheat using digital images.” J. Plant Nutr. 1999, 22:341-350) and soybeans [Glycine max L. (Merr.)] (Purcell, L. C., “Soybean canopy coverage and light interception measurements using digital imagery.” Crop Sci. 2000, 40:834-837). Through digital photography, researchers can instantaneously obtain millions of bits of information on a relatively large crop canopy. For example, a digital image taken of a crop using a 1280×960 pixel resolution contains 1,228,800 pixels, with each pixel containing independent color information about the crop.
The information contained in each digital image includes the amount of red, green and blue (“RGB”) light emitted for each pixel in the digital image. Although it may be intuitive to use the green levels of the RGB information to quantify the green color of the digital image, the intensity of red and blue will confound how green the digital image appears. To ease the interpretation of digital color data, RGB values can be converted directly to hue, saturation and brightness (“HSB”) values that are based on human perception of color. In HSB color description, hue is defined as an angle on a continuous circular scale from 0° to 360° (0°=red, 60°=yellow, 120°=green, 180°=cyan, 240°=blue, 300°=magenta), saturation is the purity of the color from 0% (gray) to 100% (fully saturated color), and brightness is the relative lightness or darkness of the color from 0% (black) to 100% (white).
It is therefore desirable to provide a system and method of determining nitrogen levels from a digital image that does not require specialized, expensive equipment.
It is further desirable to provide a system and method of determining nitrogen levels from a digital image where the digital image can easily be sent electronically, such as via email or to a web-based server, for immediate analysis.
It is still further desirable to provide a system and method of determining nitrogen levels from a digital image that integrates values over a much larger leaf sample than does the SPAD meter.
It is yet further desirable to provide a system and method of determining nitrogen levels from a digital image, which does not rely on chemical processes of measuring leaf nitrogen.
It is yet further desirable to provide a system and method of determining nitrogen levels from a digital image having a quick turn-around time to provide farmers with real-time nitrogen concentration and yield information for the crop.